On December 26, 1982, Time magazine named the personal computer “Man of the Year,” marking the first non-human recipient since its 1927 inception. In 2023 or 2024, Chat GPT or ChatGPT or Gen AI could potentially claim this title, further blurring the line between humans and machines. 

I've studied the shifting roles of digital technology in corporations for over 30 years. In the past, technology predominantly amplified company productivity. However, Gen AI ushers in a new era, one that also ignites creativity. This changes what companies do, how people contribute, and where they find a competitive edge. 

Early versions of Gen AI, like ChatGPT-4 and Google Bard, have already showcased their talents in poetry. They've also ventured into the realm of art with creations like DALL•E2 and Midjourney. Gen AI's capabilities extend to writing computer code, as seen in ChatGPT4 and IBM Watsonx, resulting in over 50% time savings. These systems have even passed basic tests in fields like law, business, and medicine. Bill Gates wrote, “The Age of AI has begun.” But the trajectories are unknown. What excites (and worries) me is not what has already been demonstrated but what could transpire in the coming three to five years if we do not take this seriously.

Gen AI isn’t a game-changer simply due to swift adoption, potential GDP growth, or prospective disruptions to society, industries, and employment. It isn’t about pitting intelligent humans against powerful machines; instead, it's about the enhanced productivity and creativity achieved when humans and machines collaborate, compared to humans working alone.

However, senior leaders—in companies and Governments—can’t and shouldn’t merely layer Gen AI onto outdated organisational and societal practices. They must sidestep the “Gen AI traps” - potential challenges or pitfalls that could arise during the adoption, implementation, and use of Gen AI.

Automation Trap: The belief that AI can or should replace all human tasks leads to potential job loss and underestimates the value of human creativity and intuition. Sure, we can rely on faster machine translation of languages, but at what cost of losing human interest in the beauty and nuance of linguistic studies? What about the structural under-employment of people with specific skills that are being rapidly automated, as the Hollywood strike foretells?

Algorithm Trap: Over-reliance on algorithmic decision-making without considering its limitations or potential biases could lead to flawed outcomes or ethical issues. Financial services is one sector that already runs on algorithms (cryptocurrency, the poster child will be healthcare with biotech and personalised medicine with gene and cell therapy tomorrow. What guardrails are in place to ensure that we train algorithms to unleash innovations?

Analytics Trap: The assumption that AI analytics will always provide perfect insights, ignoring the potential for misinterpretation or overemphasis on specific data. Yes, we can get instant personalized recommendations on what movies to watch next on Netflix what songs to listen to on Spotify, or what to buy on Amazon. But, if we do not fully understand the context and limitations of how the algorithms arrived at the results, we will increasingly be swayed by black box analytics and lose our ability to question the prescriptions.

Authenticity Trap: Losing human touch or empathy in processes automated by AI could degrade user experience or cause other unforeseen consequences. While customer service interactions could be enhanced with Chat GPT plug-ins for many pieces of advice, such as travel, personal finance, real estate, healthcare, education, and others, we should understand their consequences for social and professional interactions.

Alignment Trap: The challenge of aligning AI systems with human values and societal norms can lead to ethical controversies if not addressed. Are we creating systems that perpetuate the concentration of wealth in the hands of a few at the expense of the many? Are we creating AI systems that exacerbate the digital divide, or could gen AI be the great equalizer allowing individuals, wherever they are in the world, to achieve their potential by taking advantage of the modern tools of value creation in the palm of their hands (smartphones) that’s always connected to the ever-expanding AI cloud?

Gen AI isn’t specialised tech like 3-D printing or blockchain, it is akin to general-purpose technologies like the steam engine or electricity. Such technologies ignited swift societal and industry transformations, and Gen AI, with its unmatched scale, scope, and speed, is primed to do the same.

We risk falling into the identified traps without pausing to comprehend potential opportunities and pitfalls. Some of these traps apply at the level of individuals, others at a company or societal level. We shouldn’t halt the Gen AI wave but aim to pick a path that minimizes adverse effects. We are wise to remember, that not all will embark on this journey at the same pace or direction globally.